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<p class="MsoNormal"><span style="font-size:12.0pt">***apologies if you receive this more than once***<o:p></o:p></span></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;text-align:justify;background:white">
<span style="color:black">The Alan Turing Institute is seeking a <b>Research Associate in Infrastructure Modelling,
</b>within their <b>AI for Science and Government </b>Directorate. <o:p></o:p></span></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;text-align:justify;background:white">
<span style="color:black">We are seeking to recruit a Postdoctoral Research Associate (PDRA) to work on developing theory, methodologies and software for the creation of a computational pipeline for uncertainty quantification and certification of 3D printed
metallic products.<o:p></o:p></span></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;text-align:justify;background:white">
<span style="color:black">The considerable variability of geometry and material properties of additively manufactured parts represents a significant barrier in their rapid certification. This is currently hampering their widespread adoption beyond a few high-value,
low-volume industries. It is neither feasible nor practical to fully capture the substantial variability of the geometry and material properties resulting from the 3D printing process. Therefore, in addition to a conventional finite element model measurement
data from sensors and cameras must be utilised. We recently developed the statistical finite element method, which provides a principled approach to calibrate and update a conventional finite element model in the face of observation data. In this project,
the statistical finite element method will be applied and extended to comprehensive uncertainty quantification and certification of 3D printed products.<o:p></o:p></span></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;text-align:justify;background:white">
<span style="color:black">The ideal PDRA will possess a PhD in Computational Engineering, Applied Mathematics, Computer Science, or a closely related discipline and have a strong background in two or more of the following areas: computational structural/solid
mechanics, Bayesian inference and probabilistic machine learning, uncertainty quantification, and constitutive modelling.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:#222222;background:white">This full-time post is offered on a fixed-term contract until 31 March 2023.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal">Please find below a link to the advert, job description and application form.
<o:p></o:p></p>
<p class="MsoNormal"><u><a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fcezanneondemand.intervieweb.it%2Fturing%2Fjobs%2Fresearch_associate_infrastructure_modelling_18892%2Fen%2F&data=04%7C01%7Csdd1%40soton.ac.uk%7C90f7c9ef4e32498529b208d9c46e7826%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637756802033911553%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=agJeMwUweC2ohrPbAZDur8uFmT%2Bnqes9SJzW6GvqNao%3D&reserved=0">https://cezanneondemand.intervieweb.it/turing/jobs/research_associate_infrastructure_modelling_18892/en/</a><o:p></o:p></u></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b>Closing date</b>: 23 January 2022 at 23:59<o:p></o:p></p>
<p class="MsoNormal"><br>
Should you have any queries, please email <a href="mailto:recruitment@turing.ac.uk">
recruitment@turing.ac.uk</a>.<o:p></o:p></p>
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<p class="MsoNormal"><span style="font-size:12.0pt"><o:p> </o:p></span></p>
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<p class="MsoNormal"><span style="font-size:12.0pt;mso-fareast-language:EN-GB">__________________________________<o:p></o:p></span></p>
<p class="MsoNormal"><b><span style="font-size:12.0pt;mso-fareast-language:EN-GB">Susan Davies<o:p></o:p></span></b></p>
<p class="MsoNormal"><span style="font-size:12.0pt;mso-fareast-language:EN-GB">Coordination Manager,
<a href="https://www.southampton.ac.uk/wsi/index.page?">Web Science Institute</a><o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;mso-fareast-language:EN-GB">University Liaison Manager,
<a href="https://www.southampton.ac.uk/wsi/alan-turing-institute/alan-turing-institute.page">
The Alan Turing Institute</a><o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;mso-fareast-language:EN-GB">Web Science Institute<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;mso-fareast-language:EN-GB">University of Southampton<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;mso-fareast-language:EN-GB">Southampton SO17 1BJ<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;mso-fareast-language:EN-GB">M 07768 266464<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;mso-fareast-language:EN-GB"><a href="https://www.southampton.ac.uk/wsi/index.page">https://www.southampton.ac.uk/wsi</a><o:p></o:p></span></p>
<p class="MsoNormal"><span style="mso-fareast-language:EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><i><span style="font-size:12.0pt;mso-fareast-language:EN-GB">My working days are Monday to Thursday.<o:p></o:p></span></i></b></p>
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